模型

浏览来自所有提供商的 5 个标准化 LLM 模型

显示第 1–5 项,共 5 个模型

Nemotron 3 Ultra

美国

NVIDIA's flagship open 550B-parameter Mixture-of-Experts model with 55B active parameters, built for frontier reasoning and orchestration in long-running agentic systems. Features hybrid Mamba-Transformer architecture, LatentMoE routing, multi-token prediction, and NVFP4 precision for 5x higher throughput. Achieves 30% lower cost-to-task-completion on agentic benchmarks. Supports 1M+ token context window with 95% accuracy on Ruler@1M.

上下文
1.0M
发布日期
2026年6月

Llama 4 Maverick

美国

Meta's quality-focused MoE model with 17B active parameters (400B total, 128 experts). Targets quality-critical tasks with benchmark scores competitive with GPT-4o and Gemini 2.5 Pro.

上下文
1.0M
发布日期
2025年4月

Llama 4 Scout

美国

Meta's efficient MoE model with 17B active parameters (109B total, 16 experts). Supports up to 10M token context — the longest of any production model. Strong performance on reasoning and multilingual tasks.

上下文
10.0M
发布日期
2025年4月

Llama 3.3 70B Instruct

美国

Meta's flagship open-weight model with 70 billion parameters. Strong multilingual capabilities with competitive performance on reasoning and coding benchmarks. Available for self-hosting and through various inference providers.

上下文
131K
发布日期
2024年12月

Llama 3.1 8B Instruct

美国

Meta's efficient open-weight model with 8 billion parameters from the Llama 3.1 family. Optimized for instruction following with strong performance on general tasks, coding, and multilingual benchmarks. Ideal for cost-effective deployment and edge inference scenarios.

上下文
131K
发布日期
2024年7月